Cellular automata models for vegetation dynamics

Balzter, Heiko; Braun, Paul; Köhler, W.

doi:10.1016/s0304-3800(97)00202-0

Cited by 253 publications

(118 citation statements)

References 38 publications

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“…These models have been increasingly unable to explain plant community dynamics (e.g., in Neotropic forests, fields and grasslands: see chapters in Myster 2007, Myster 2012a, Myster 2017a and so many researchers have turned to plant-plant replacement (Horn 1976, Grubb 1977, Busing 1996, Poulson and Platt 1996, Balzter et al 1998, Kneeshaw and Bergerson, 1998, Pacala et al 1998) as a new and better paradigm (Myster 2012b). Plant-plant replacements are not large-scale events like disturbances, nor do they occur over entire patches, but instead happen at the scale of individual plants of potentially different sizes throughout plant communities (Myster 2012b).…”

Section: A New Paradigmmentioning

confidence: 99%

The nine classes of plant-plant replacement

Myster¹

2018

IEE

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Current models of plant community dynamics have fallen short both of conceptualizing plant communities well and of giving researchers a tool that accurately predicts their dynamics. Here I present a new idea of how that conceptual model should be constructed. I begin with the observation that space is a critical component of plant life and how it changes determines-to a large extenthow individual plants change. I then define that space as consisting of the phyto-space, which the phyto-mass (biomass plus necromass) occupies, and the neighborhood space around that phyto-space where a plant can influence, and be influenced by, other plants. I posit that it is how plants that make up a community replace themselves over time, as their phyto-spaces and neighborhood spaces change, that is the fundamental process of plant community dynamics. Those plant-plant replacements fall into nine distinct classes that extend the concept of replacement to include new space created not just by whole plant mortality, but also by plant tissue loss. Finally, I suggest that because most plant-plant replacements involve seeds, seedlings and saplings, the mechanisms and tolerances of predation, pathogens, germination, herbivory and seedling/sapling competition will be most critical in determining the plant-plant replacements in any plant community and its resulting dynamics.

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Section: A New Paradigmmentioning

confidence: 99%

The nine classes of plant-plant replacement

Myster¹

2018

IEE

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“…The rich variety of CCA-and CA-based models that has been developed during the last decade for describing various spatial biological phenomena such as epidemics [6,14,28], population dynamics [3,5], tumor growth [13,23,24], biofilm development [21,22] and many other phenomena [10,25] is illustrative for the suitability of such models to mimic complex bioprocesses. In a forthcoming work, Baetens and De Baets [2] propose a generalized CCA for modelling various biological processes that are traditionally described by means of PDEs.…”

Section: The Modelmentioning

confidence: 99%

Tracking Uncertainty in a Spatially Explicit Susceptible-Infected Epidemic Model

Baetens

Baets

2010

Lecture Notes in Computer Science

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Abstract. In this paper we conceive an interval-valued continuous cellular automaton for describing the spatio-temporal dynamics of an epidemic, in which the magnitude of the initial outbreak and/or the epidemic properties are only imprecisely known. In contrast to well-established approaches that rely on probability distributions for keeping track of the uncertainty in spatio-temporal models, we resort to an interval representation of uncertainty. Such an approach lowers the amount of computing power that is needed to run model simulations, and reduces the need for data that are indispensable for constructing the probability distributions upon which other paradigms are based.

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“…1997; Balzter et al, 1998) but they describe clonal expansion on a grid basis using simple empirical rules, or random processes. They can be used to predict patterns on a larger scale, but being empirical, they do not provide mechanistic insight.…”

Section: Comparison With Other Modelsmentioning

confidence: 99%

Modelling the clonal growth of the rhizomatous macrophyte Potamogeton perfoliatus

Wolfer

Nes

Straile

2006

Ecological Modelling

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Macrophytes play a crucial role in the functioning of lake ecosystems. Until now most macrophyte models neglected the fact that the majority of macrophyte species expand clonally during the growing season. Inclusion of a detailed description of clonal growth in models can facilitate our understanding of space occupation and patch expansion and predict future macrophyte development. "CLOMO" is an individual-based model which includes a detailed, spatially explicit description of rhizome formation and clone expansion as well as a realistic description of photosynthesis including light limitation and temperature. The model also accounts for transfers of energy or resources between different parts of the clone ("clonal integration").Although the clonal growth of macrophytes is complex and poorly known, the first model results for the macrophyte species Potamogeton perfoliatus were promising and compared well with the field data. The model can produce growth networks very similar to those found in the field. A Monte Carlo sensitivity analysis showed systematically which parameters have the largest effect on the architecture and expansion of the clones.The application of the model provided new insights into growth dynamics and patch development: (1) the model showed that a lack of branching will lead to the extinction of the clone after a certain number of years. This is due to the fact that the reproductive organs (turions) are formed at the end of a branch and even a small turion mortality will cause a reduction in surviving plant numbers; (2) the growth of rhizome axes relative to those in the previous year determines the patch density and patch expansion rate. Reversing rhizomes lead to compact patch growth whereas continuing rhizomes lead to loose aggregates.

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Cellular automata models for vegetation dynamics

Cited by 253 publications

References 38 publications

The nine classes of plant-plant replacement

The nine classes of plant-plant replacement

Tracking Uncertainty in a Spatially Explicit Susceptible-Infected Epidemic Model

Modelling the clonal growth of the rhizomatous macrophyte Potamogeton perfoliatus

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